bluemira.equilibria.optimisation.harmonics.harmonics_constraints
================================================================

.. py:module:: bluemira.equilibria.optimisation.harmonics.harmonics_constraints

.. autoapi-nested-parse::

   Harmonics constraint functions.



Classes
-------

.. autoapisummary::

   bluemira.equilibria.optimisation.harmonics.harmonics_constraints.SphericalHarmonicConstraint
   bluemira.equilibria.optimisation.harmonics.harmonics_constraints.ToroidalHarmonicConstraint


Module Contents
---------------

.. py:class:: SphericalHarmonicConstraint(ref_harmonics: numpy.typing.NDArray[numpy.float64], r_t: float, sh_coil_names: list, tolerance: float | numpy.typing.NDArray | None = None, smallest_tol: float = 1e-06, constraint_type: str = 'equality', *, invert: bool = False)

   Bases: :py:obj:`bluemira.equilibria.optimisation.constraints.UpdateableConstraint`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.harmonics.harmonics_constraints.SphericalHarmonicConstraint
      :parts: 1
      :private-bases:


   Spherical harmonic constraints for the desired core plasma
   of a spherical tokamak equilibria.

   :param ref_harmonics: Initial harmonic amplitudes obtained from desired core plasma
                         (Returned by spherical_harmonic_approximation)
   :param r_t: (Returned by spherical_harmonic_approximation)
   :type r_t: float
   :param sh_coil_names: Names of the coils to use with SH approximation
                         (Returned by spherical_harmonic_approximation)
   :param tolerance: Tolerance with which the constraint(s) will be met


   .. py:attribute:: constraint_type
      :value: 'equality'



   .. py:attribute:: tolerance
      :value: None



   .. py:attribute:: target_harmonics


   .. py:attribute:: max_degree


   .. py:attribute:: invert
      :value: False



   .. py:attribute:: sh_coil_names


   .. py:attribute:: r_t


   .. py:attribute:: _args


   .. py:property:: control_coil_names

      The names of the allowed control coils when using the
      SH approximation constraints.


   .. py:method:: prepare(equilibrium: bluemira.equilibria.equilibrium.Equilibrium, *, I_not_dI=False, fixed_coils=False)

      Prepare the constraint for use in an equilibrium optimisation problem.

      :raises ValueError: Constraint requires fixed coils



   .. py:method:: control_response(coilset: bluemira.equilibria.coils.CoilSet) -> numpy.ndarray

      Calculate control response of a CoilSet to the constraint.

      :returns: The coil harmonic amplitude matrix



   .. py:method:: evaluate(_eq: bluemira.equilibria.equilibrium.Equilibrium) -> numpy.typing.NDArray[numpy.float64]

      Calculate the value of the constraint in an Equilibrium.



   .. py:method:: f_constraint() -> bluemira.equilibria.optimisation.harmonics.harmonics_constraint_functions.SphericalHarmonicConstraintFunction

      Constraint function.



   .. py:method:: plot(ax)

      Plot the constraint onto an Axes.



.. py:class:: ToroidalHarmonicConstraint(th_result: bluemira.equilibria.optimisation.harmonics.toroidal_harmonics_approx_functions.ToroidalHarmonicsSelectionResult, relative_tolerance_cos: float | numpy.typing.NDArray[numpy.float64] = 0.001, relative_tolerance_sin: float | numpy.typing.NDArray[numpy.float64] = 0.001, constraint_type: str = 'equality', weights: float | numpy.ndarray = 1.0)

   Bases: :py:obj:`bluemira.equilibria.optimisation.constraints.UpdateableConstraint`

   .. autoapi-inheritance-diagram:: bluemira.equilibria.optimisation.harmonics.harmonics_constraints.ToroidalHarmonicConstraint
      :parts: 1
      :private-bases:


   Toroidal harmonic constraints for the desired core plasma
   of a conventional aspect ratio stokamak equilibria.

   :param ref_harmonics: Initial harmonic amplitudes obtained from desired core plasma
                         (Returned by toroidal_harmonic_approximation)
   :param th_params: ToroidalHarmonicsParams dataclass containing necessary parameters for use in TH
                     approximation
   :param tolerance: Tolerance with which the constraint(s) will be met


   .. py:attribute:: constraint_type
      :value: 'equality'



   .. py:attribute:: cos_degrees_chosen


   .. py:attribute:: sin_degrees_chosen


   .. py:attribute:: th_params


   .. py:attribute:: target_value


   .. py:attribute:: weights
      :value: 1.0



   .. py:attribute:: _args


   .. py:property:: control_coil_names

      The names of the allowed control coils when using the
      TH approximation constraints.


   .. py:method:: prepare(equilibrium: bluemira.equilibria.equilibrium.Equilibrium, *, I_not_dI=False, fixed_coils=True)

      Prepare the constraint for use in an equilibrium optimisation problem.

      :raises ValueError: Constraint requires fixed coils



   .. py:method:: control_response(coilset: bluemira.equilibria.coils.CoilSet) -> numpy.ndarray

      Calculate control response of a CoilSet to the constraint.

      :returns: The coil harmonic amplitude matrix



   .. py:method:: evaluate(_eq: bluemira.equilibria.equilibrium.Equilibrium) -> tuple[numpy.typing.NDArray[numpy.float64], numpy.typing.NDArray[numpy.float64]]

      Calculate the value of the constraint in an Equilibrium.



   .. py:method:: f_constraint() -> bluemira.equilibria.optimisation.harmonics.harmonics_constraint_functions.ToroidalHarmonicConstraintFunction

      Constraint function.



   .. py:method:: plot(ax)

      Plot the constrained region onto an Axes.



   .. py:method:: __len__() -> int

      Length of TH constraint.